Search Results for "parallel genetic algorithm"
Sort By:
49 projects for "parallel genetic algorithm" with 2 filters applied:
-
Our Free Plans just got better! | Auth0You asked, we delivered! Auth0 is excited to expand our Free and Paid plans to include more options so you can focus on building, deploying, and scaling applications without having to worry about your security. Auth0 now, thank yourself later.
-
Create and run cloud-based virtual machines.Computing infrastructure in predefined or custom machine sizes to accelerate your cloud transformation. General purpose (E2, N1, N2, N2D) machines provide a good balance of price and performance. Compute optimized (C2) machines offer high-end vCPU performance for compute-intensive workloads. Memory optimized (M2) machines offer the highest memory and are great for in-memory databases. Accelerator optimized (A2) machines are based on the A100 GPU, for very demanding applications.
-
1
Motofit co-refines Neutron and X-ray reflectometry data, using the Abeles matrix / Parratt recursion and least squares fitting (Genetic algorithm or Levenberg Marquardt). It works in the IGOR Pro environment (TM Wavemetrics).
-
2
The ASCO project aims to bring circuit optimization capabilities to existing SPICE simulators using a high-performance parallel differential evolution (DE) optimization algorithm. It supports Eldo, HSPICE, LTspice, Spectre, and Qucs.
-
3
Geophysical Library is a C++-library to handle geophysical data. At the moment the focus is on magnetotelluric and seismic data. It also includes a genetic algorithm for data inversion, signal processing and statistics routines.
-
4
Xoptfoil
Airfoil optimization with Xfoil
Airfoil optimization using the highly-regarded Xfoil engine for aerodynamic calculations. Starting with a seed airfoil, Xoptfoil uses particle swarm, genetic algorithm and direct search methodologies to perturb the geometry and maximize performance. The user selects a number of operating points over which to optimize, desired constraints, and the optimizer does the rest. -
Award-Winning Medical Office Software Designed for Your SpecialtyRXNT is an ambulatory healthcare technology pioneer that empowers medical practices and healthcare organizations to succeed and scale through innovative, data-backed, AI-powered software.
-
5
The source code has been migrated and is now hosted on Github: https://github.com/jenetics/jenetics Jenetics is an advanced Genetic Algorithm, Evolutionary Algorithm and Genetic Programming library, respectively, written in modern day Java. It is designed with a clear separation of the several algorithm concepts, e. g. Gene, Chromosome, Genotype, Phenotype, Population and fitness Function. Jenetics allows you to minimize or maximize the given fitness function without tweaking it. ...
-
6
PF_HP
Prediction of proteinfolding in 2D HP model
Even in the simplified two dimensional HP-model (hydrophob/polar) the prediction of proteinfolding is NP complete. We implement a brute force algorithm with serial and parallel execution to solve short inputs of HP sequences (0-1 bitstrings). Selbst im vereinfachten zweidimensionalen HP-Modell (hydrophob/polar) ist die Proteinfaltung bereits NP-vollständig. Hier implementieren wir einen brute-force Algorithmus zur Lösung kurzer Eingabesequenzen (0-1-Bitstrings) für die Proteinfaltung. ... -
7
As of August 2018 Spheral++ has moved to Github -- please see the current repository at https://github.com/jmikeowen/spheral We are leaving a frozen version here on SourceForge for historical reasons. Spheral++ provides a steerable parallel environment for performing coupled hydrodynamical & gravitational numerical simulations. Hydrodynamics and gravity are modelled using particle based methods (SPH and N-Body).
-
8
popt4jlib
Parallel Optimization Library for Java
popt4jlib is an open-source parallel optimization library for the Java programming language supporting both shared memory and distributed message passing models. Implements a number of meta-heuristic algorithms for Non-Linear Programming, including Genetic Algorithms, Differential Evolution, Evolutionary Algorithms, Simulated Annealing, Particle Swarm Optimization, Firefly Algorithm, Monte-Carlo Search, Local Search algorithms, Gradient-Descent-based algorithms, as well as some well-known network flow and other graph algorithms. ... -
9
Opt4J
Modular Java framework for meta-heuristic optimization
Opt4J is an open source Java-based framework for evolutionary computation. It contains a set of (multi-objective) optimization algorithms such as evolutionary algorithms (including SPEA2 and NSGA2), differential evolution, particle swarm optimization, and simulated annealing. The benchmarks that are included comprise ZDT, DTLZ, WFG, and the knapsack problem. The goal of Opt4J is to simplify the evolutionary optimization of user-defined problems as well as the implementation of arbitrary... -
Dun and Bradstreet Connect simplifies the complex burden of data managementThe amount, speed, and types of data created in today’s world can be overwhelming. With D&B Connect, you can instantly benchmark, enrich, and monitor your data against the Dun & Bradstreet Data Cloud to help ensure your systems of record have trusted data to fuel growth.
-
10
GeneticAlgorithms
Framework for using the Genetic Algorithms optimization heuristic.
GeneticAlgorithms is a simple and lightweight framework to implement an optimization heuristic following the Genetic Algorithms model. A genetic algorithm mimics the natural processes of evolution, selection and "survival of the fittest". This framework is intuitive and good integrated with Java 1.5 SDK and later. -
11
SWAPHI-LS: Alignment on Xeon Phi Cluster
Smith-Waterman long DNA sequence alignment on Xeon Phi clusters
The first parallel Smith-Waterman algorithm exploiting Intel Xeon Phi clusters to accelerate the alignment of long DNA sequences. This algorithm is written in C++ (with a set of SIMD intrinsic extensions), OpenMP and MPI. The performance evaluation revealed that our algorithm achieves very stable performance, and yields a performance of up to 30.1 GCUPS on a single Xeon Phi and up to 111.4 GCUPS on four Xeon Phis sharing a host. -
12
SWAPHI: Smith-Waterman on Intel Xeon Phi
The first protein sequence database search on shared-host Xeon Phis
The first parallel algorithm to accelerate the Smith-Waterman protein database search on shared-host multiple Intel Xeon Phi coprocessors. By searching against the UniProtKB/TrEMBL database, SWAPHI achieves a performance of up to 58.8 billion cell updates per second (GCUPS) on a single Xeon Phi and up to 228.4 GCUPS on four Xeon Phis. -
13
gametes
Generate complex SNP models and heterogeneous datasets
Genetic Architecture Model Emulator for Testing and Evaluating Software (GAMETES) is an algorithm for the generation of complex single nucleotide polymorphism (SNP) models for simulated association studies. GAMETES is designed to generate epistatic models which we refer to as pure and strict, that constitute the worst-case in terms of detecting disease associations, since such associations may only be observed if all n-loci are included in the disease model. -
14
PyGAO
Genetic Algorithm Optimization for Python
A simple interface for performing genetic algorithm optimization for numerical problems. I am starting with a stripped-down version, where a solution can be described using a single vector of float numbers. Eventually, I will expand to more generic data structures and add multiple-species search options. For the time being, I have no plans of developing a GUI. For now, this is strictly a computational module. -
15
Java Evolutionary Computation Library
As of 2012-12-18, this project may now be found at Google Code.
As of 2012-12-18, this project may now be found at http://http://code.google.com/p/paba JECO is a Evolutionary Computation Library deveoloped in Java. It includes a variety of evolutionary optimization techniques such as genetic algorithm, genetic programming, evolutionary mapping methods, particle swarm optimization, ant colonies, etc. -
16
Darwin 2: Java Framework for Evolutionary Computation (genetic algorithm, GA). A true framework with out-of-the-box functionality and extensibility of all classes. Interface-based pattern with dependency-injection to configure components.
-
17
DecGPU: CUDA-based Error Correction
The first distributed and parallel short-read error corrector on GPUs
DecGPU (Distributed Error correction on GPUs) is a parallel and distributed error correction algorithm for large-scale short read assembly. It is implemented using CUDA C++ and MPI, running on a GPU cluster. -
18
PyPedal is a Python module that provides tools for the manipulation of pedigrees, simple visualization of pedigrees, and the calculation of measures of genetic diversity from pedigrees.
-
19
CRFSharp
CRFSharp is a .NET(C#) implementation of Conditional Random Field
CRFSharp(aka CRF#) is a .NET(C#) implementation of Conditional Random Fields, an machine learning algorithm for learning from labeled sequences of examples. It is widely used in Natural Language Process (NLP) tasks, for example: word breaker, postagging, named entity recognized, query chunking and so on. CRF#'s mainly algorithm is the same as CRF++ written by Taku Kudo. It encodes model parameters by L-BFGS. Moreover, it has many significant improvement than CRF++, such as totally parallel encoding, optimizing memory usage and so on. ... -
20
Alkindus is an automated solver for short monoalphabetic substitution ciphers without word divisions.
-
21
This project is a complete cross-platform (Windows, Linux) framework for Evolutionary Computation in pure python. See the project site at http://pyevolve.sourceforge.net or the blog at http://pyevolve.sourceforge.net/wordpress
-
22
This library is a lightweight implementation of genetic algorithm, contains the most popular types of chromosomes and the basic algorithms for selection, elitism, crossing and mutation.
-
23
This easy to run and change program for developers, it contains several evolutionary based strategies allowing you try among some function samples
-
24
Java API for implementing any kind of Genetic Algorithm and Genetic Programming applications quickly and easily. Contains a wide range of ready-to-use GA and GP algorithms and operators to be plugged-in or extended. Includes Tutorials and Examples.
-
25
